Battery management systems face usually different challenging tasks. One of the most important concerns the on-board evaluation of the total battery capacity in electric and hybrid electric vehicles. This is due to the fact that the battery capacity has to be computed without necessarily discharging the battery entirely starting from a fully charged state. In fact, during the vehicle operations, the discharge process is mainly carried out in a dynamic condition under variable current rates and temperature. Selecting a method to be used in this process has poised a challenge mainly for lithium iron phosphate cells.
In a recent paper published in Journal of Power Sources, Andrea Marongiu and colleagues estimated lithium iron phosphate batteries capacity by means of half-cell curves. Their research mainly focused on developing a new approach that is based on the detection of the actual degradation mechanisms by collecting plateau information.
First, a model was developed and introduced which described the characteristics of the electrode voltage curves of the lithium iron phosphate cells and the impact of aging on the full cell voltage. A description of the main degradation mechanisms that can occur during the lifetime of the lithium iron phosphate cell and a model capable of describing the effects of degradation on the electrode and on the full cell voltage curves were presented. The research team then introduced a new battery management system structure with an implemented algorithm for on-board capacity estimation.
The results reported in the work show that not all the information from the voltage plateaus has to be collected at the same time although the collection phases have to be over short duration intervals. The new introduced algorithm is simple to parametrize, since only the characteristics of the cell in a fresh state are needed, in terms of stoichiometry and half-cell voltage curves. Eventually, both during charge and discharge the algorithm is able to correctly track the actual battery capacity with an error of approximately 1%. Also, the new proposed BMS structure is designed in a way that part of the novel methodology can run offline (not-real time). This means that the approach can be implemented in cheap microcontrollers, as it does not need to be executed in real time.
The method presented in this paper is valid for lithium iron phosphate /G cells, primarily due to the need of collecting data of plateaus, which is one of the main features of this type of cells. Nevertheless, the proposed model and the approach shown in the literature have a general formulation, which demonstrate the benefit of the tracked aging information for different lithium-ion technologies and additional application scopes.
Andrea Marongiu1,3, Nsombo Nlandi1,3, Yao Rong1,3, Dirk Uwe Sauer1,2,3. On-board capacity estimation of lithium iron phosphate batteries by means of half-cell curves. Journal of Power Sources volume 324 (2016) pages 158-169.Show Affiliations
- Electrochemical Energy Conversion and Storage Systems Group, Institute for Power Electronics and Electrical Drives (ISEA), RWTH Aachen University, Jägerstrasse 17/19, D-52066 Aachen, Germany
- Institute for Power Generation and Storage Systems (PGS), E.ON ERC, RWTH Aachen University, Mathieustrasse, D-52074 Aachen, Germany
- Jülich Aachen Research Alliance, JARA-Energy, Germany
Go To Journal of Power Sources